Psychometrics MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| check_computation_capabilitiesA | Report whether local Python and the fixed R/eRm Rasch engine are available. |
| inspect_response_dataB | Audit response shape, missingness, categories, ranges, and zero-variance items. |
| ctt_item_analysisC | Compute item summaries, item-rest correlations, raw alpha, and SEM with warnings. |
| descriptive_statisticsB | Summarize numeric variables with sample flow, missingness, and robust boundaries. |
| correlation_matrixA | Compute Pearson or Spearman correlations with explicit missing-data handling. |
| plan_psychometric_analysisC | Create a measurement-aware analysis sequence from the intended use and design. |
| rasch_modelA | Fit a fixed dichotomous Rasch model with eRm::RM; arbitrary code is never accepted. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
The core analysis tools are mostly distinct, but inspect_response_data, descriptive_statistics, and ctt_item_analysis all touch on summarizing data, missingness, and item-level properties. Descriptions help clarify intent, yet an agent could still hesitate between an audit and a general descriptive summary.
Tool names use snake_case throughout and are readable, but they mix verb-led names like inspect_response_data and plan_psychometric_analysis with noun-led names like correlation_matrix and rasch_model. The inconsistency is mild but prevents a clear predictable verb_noun convention.
Seven tools is well-scoped for a psychometrics-focused server covering environment checks, data inspection, descriptive stats, correlations, CTT, planning, and Rasch modeling. Each tool earns its place without bloating the surface.
The server covers a coherent CTT-plus-Rasch workflow from planning through data auditing, descriptives, correlations, item analysis, and model fitting. Minor gaps exist such as no polytomous IRT or visualization tools, but the core measurement workflow is not blocked.